Publication: Automated Classification of Criminal and Violent Activities in Thailand from Online News Articles
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Issued Date
2021-01-21
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2-s2.0-85105866006
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Mahidol University
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SCOPUS
Bibliographic Citation
KST 2021 - 2021 13th International Conference Knowledge and Smart Technology. (2021), 170-175
Suggested Citation
Tipajin Thaipisutikul, Suppawong Tuarob, Siripen Pongpaichet, Amornsri Amornvatcharapong, Timothy K. Shih Automated Classification of Criminal and Violent Activities in Thailand from Online News Articles. KST 2021 - 2021 13th International Conference Knowledge and Smart Technology. (2021), 170-175. doi:10.1109/KST51265.2021.9415789 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/76680
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Title
Automated Classification of Criminal and Violent Activities in Thailand from Online News Articles
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Abstract
Criminal and violent activities are a universal concern that affects a society's nature of life and economic dynamics. With dramatically increasing crime rates, law enforcement agencies have begun to show attention in utilizing machine learning approaches to analyze crime patterns to protect their communities. However, there are only a few studies that carried out experiments to classify Thai crime news articles into their proper categories. Also, the comparison of various machine learning algorithms toward this task has still been under-investigated. Therefore, in this paper, we aim to develop a framework to automate the classification and visualization of criminal and violent activities from online Thai news articles. Six classifiers are employed to classify crime news articles into one of the five crime categories including Burglary, Drug, Murder, Accident, and Corruption. The results have shown that Support Vector Machine and Logistic Regression approaches outperform other classifiers in terms of Accuracy, Precision, Recall, and F-Measure metrics.